ArticleJournal of chemical theory and computation2022
Large Scale Study of Ligand-Protein Relative Binding Free Energy Calculations: Actionable Predictions from Statistically Robust Protocols.
Article in Journal of chemical theory and computation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Absolute Binding Free Energy Calculations between the SARS-CoV-2 Main Protease and 130 Drug Leads Using Implicit Ligand Theory.Journal of chemical information and modeling · 2026Article
- Uncertainty Quantification forChemical reviews · 2026Review
- Integrated framework for targeting dynamic penicillin-binding protein 2a via ensemble structural biology and deep generative modeling.Frontiers in microbiology · 2026Article
- Free Energy Perturbation Simulations Measure the Change in Binding Affinity of the Aβ25-35 Peptide to the Zwitterionic Bilayer Caused by Oxidation.Journal of chemical information and modeling · 2025Article
- Rapid, accurate, and reproduciblemSphere · 2025Article
- In Vitro and In Silico Evaluation of the Potential Anti-Prostate Cancer Activity ofInternational journal of molecular sciences · 2025Article
- Estimation of Absolute Binding Free Energies for Drugs That Bind Multiple Proteins.Journal of chemical information and modeling · 2025Article
- Impact of Varying Velocities and Solvation Boxes on Alchemical Free-Energy Simulations.Journal of chemical information and modeling · 2025Article
- Robust Automated Truncation Point Selection for Molecular Simulations.Journal of chemical theory and computation · 2025Article
- Equilibrium and Nonequilibrium Ensemble Methods for Accurate, Precise and Reproducible Absolute Binding Free Energy Calculations.Journal of chemical theory and computation · 2025Article
- Accurate prediction of protein-ligand interactions by combining physical energy functions and graph-neural networks.Journal of cheminformatics · 2024Article
- Automated Adaptive Absolute Binding Free Energy Calculations.Journal of chemical theory and computation · 2024Article
- Application of an alchemical free energy method for the prediction of thermostable DuraPETase variants.Applied microbiology and biotechnology · 2024Article
- Ensemble-Based Approaches Ensure Reliability and Reproducibility.Journal of chemical information and modeling · 2023Article
- Comparison of Equilibrium and Nonequilibrium Approaches for Relative Binding Free Energy Predictions.Journal of chemical theory and computation · 2023Article
- Computed Protein-Protein Enthalpy Signatures as a Tool for Identifying Conformation Sampling Problems.Journal of chemical information and modeling · 2023Article
- Comparison of Receptor-Ligand Restraint Schemes for Alchemical Absolute Binding Free Energy Calculations.Journal of chemical theory and computation · 2023Article
- TIES 2.0: A Dual-Topology Open Source Relative Binding Free Energy Builder with Web Portal.Journal of chemical information and modeling · 2023Article
- ACES: Optimized Alchemically Enhanced Sampling.Journal of chemical theory and computation · 2023Article
- Open Force Field BespokeFit: Automating Bespoke Torsion Parametrization at Scale.Journal of chemical information and modeling · 2022Article
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2 authors.
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Abstract
The accurate and reliable prediction of protein-ligand binding affinities can play a central role in the drug discovery process as well as in personalized medicine. Of considerable importance during lead optimization are the alchemical free energy methods that furnish an estimation of relative binding free energies (RBFE) of similar molecules. Recent advances in these methods have increased their speed, accuracy, and precision. This is evident from the increasing number of retrospective as well as prospective studies employing them. However, such methods still have limited applicability in real-world scenarios due to a number of important yet unresolved issues. Here, we report the findings from a large data set comprising over 500 ligand transformations spanning over 300 ligands binding to a diverse set of 14 different protein targets which furnish statistically robust results on the accuracy, precision, and reproducibility of RBFE calculations. We use ensemble-based methods which are the only way to provide reliable uncertainty quantification given that the underlying molecular dynamics is chaotic. These are implemented using TIES (Thermodynamic Integration with Enhanced Sampling). Results achieve chemical accuracy in all cases. Ensemble simulations also furnish information on the statistical distributions of the free energy calculations which exhibit non-normal behavior. We find that the "enhanced sampling" method known as replica exchange with solute tempering degrades RBFE predictions. We also report definitively on numerous associated alchemical factors including the choice of ligand charge method, flexibility in ligand structure, and the size of the alchemical region including the number of atoms involved in transforming one ligand into another. Our findings provide a key set of recommendations that should be adopted for the reliable application of RBFE methods.
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